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SPRINGER COMPLEXITY LECTURE

Lada A. Adamic

Facebook

Lada A. Adamic is a research scientist on the Core Data Science Team at Facebook. Her research interests center on information dynamics in networks: how information diffuses, how it can be found, and how it influences the evolution of a network's structure. Previously, she was an associate professor in the School of Information and the Center for the Study of Complex Systems at the University of Michigan. She has received an NSF CAREER award, a University of Michigan Henry Russell award, and the 2012 Lagrange Prize in Complex Systems.

The strange paths that information takes

A primary function of online social networks is to share information, and it is in online social networks, and in particular on Facebook, where we can start to trace the paths the information takes across social ties, uncovering several interesting characteristics. To some extent, the reach, if not the exact path of the information, is predictable. One can make the prediction based on the content, the initiator, and the early diffusion structure and timing. Some content will be primarily broadcast, while certain types will make many steps, being passed from person to person to person. A category of information that is propagated through multiple steps is that of rumors. The spread will depend on the rumor's veracity, as will the likelihood that their telling will be retracted. Even more curiously, rumors can experience a resurgence in popularity from near dormancy. These peaks may correspond to the same exact rumor, or very likely they will contain one or more alterations. In fact, by studying information that has been copied from one status update to another we find frequent mutations, in a process akin to biological evolution. These and other interesting aspects of information diffusion in networks will be discussed in the talk.